package net.lmc.realtime.jtp.dws.log.job;

import net.lmc.realtime.jtp.dws.log.utils.AnalyzerUtil;
import org.apache.flink.configuration.Configuration;
import org.apache.flink.table.annotation.DataTypeHint;
import org.apache.flink.table.annotation.FunctionHint;
import org.apache.flink.table.api.EnvironmentSettings;
import org.apache.flink.table.api.Table;
import org.apache.flink.table.api.TableEnvironment;
import org.apache.flink.table.functions.TableFunction;
import org.apache.flink.types.Row;

import java.util.List;

public class JtpTrafficSearchKeywordMinuteWindowDwsJob {
    public static void main(String[] args) {
        //执行环境
        TableEnvironment tabEnv = getTableEnv();

        //输出表 映射结果到kafka消息队列
        createInputTable(tabEnv);

        //数据处理
        Table reportTable = handle(tabEnv);

        //输出表 映射到Clickhouse
        createOutputTable(tabEnv);

        //保存数据
        saveToClickHouse(tabEnv,reportTable);
    }

    private static void saveToClickHouse(TableEnvironment tabEnv, Table reportTable) {
        // 先注册临时表
        tabEnv.createTemporaryView("report_table", reportTable);
        // 插入数据
        tabEnv.executeSql(
                "INSERT INTO dws_traffic_search_keyword_window_report_clickhouse_sink\n" +
                        "SELECT\n" +
                        "    DATE_FORMAT(window_start_time, 'yyyy-MM-dd HH:mm:ss') AS window_start_time\n" +
                        "    , DATE_FORMAT(window_end_time, 'yyyy-MM-dd HH:mm:ss') AS window_end_time\n" +
                        "    , keyword\n" +
                        "    , keyword_count\n" +
                        "    , ts\n" +
                        "FROM report_table"
        );
    }


    private static void createOutputTable(TableEnvironment tabEnv) {
        tabEnv.executeSql(
                "CREATE TABLE dws_traffic_search_keyword_window_report_clickhouse_sink(\n" +
                        "    `window_start_time` STRING COMMENT '窗口开始日期时间',\n" +
                        "    `window_end_time` STRING COMMENT '窗口结束日期时间',\n" +
                        "    `keyword` STRING COMMENT '搜索关键词',\n" +
                        "    `keyword_count` BIGINT COMMENT '搜索关键词被搜索次数',\n" +
                        "    `ts` BIGINT COMMENT '数据产生时间戳'\n" +
                        ") WITH (\n" +
                        "    'connector' = 'clickhouse',\n" +
                        "    'url' = 'jdbc:clickhouse://node103:8123/jtp_log_report',\n" +
                        "    'table' = 'dws_traffic_search_keyword_window_report',\n" +
                        "    'username' = 'default',\n" +
                        "    'password' = '',\n" +
                        "    'format' = 'json'\n" +
                        ")"
        );
    }

    private static Table handle(TableEnvironment tabEnv) {
        // s1-获取搜索词和搜索时间
        Table searchLogTable = tabEnv.sqlQuery(
                "SELECT\n" +
                        "    page['item'] AS full_word\n" +
                        "    , row_time\n" +
                        "FROM dwd_traffic_page_log_kafka_source\n" +
                        "WHERE page['item'] IS NOT NULL\n" +
                        "    AND page['last_page_id'] = 'search'\n" +
                        "    AND page['item_type'] = 'keyword'"
        );
         //searchLogTable.execute().print();
        tabEnv.createTemporaryView("search_log_table", searchLogTable);

        // s2-使用自定义UDTF函数，对搜索词进行中文分词
        tabEnv.createTemporarySystemFunction("ik_analyzer_udtf", IkAnalyzerFunction.class);
        Table wordLogTable = tabEnv.sqlQuery(
                "SELECT\n" +
                        "    full_word\n" +
                        "    , keyword\n" +
                        "    , row_time\n" +
                        "FROM search_log_table,\n" +
                        "   LATERAL TABLE(ik_analyzer_udtf(full_word)) AS T(keyword)"
        );
        //wordLogTable.execute().print();
        tabEnv.createTemporaryView("word_log_table", wordLogTable);

         //s3-设置窗口进行分组、聚合计算
        Table reportTable = tabEnv.sqlQuery("SELECT\n" +
                "    TUMBLE_START(row_time, INTERVAL '10' second) AS window_start_time,\n" +
                "    TUMBLE_END(row_time, INTERVAL '10' second) AS window_end_time, \n" +
                "    keyword,\n" +
                "    count(keyword) AS keyword_count,\n" +
                "    UNIX_TIMESTAMP() * 1000 AS ts\n" +
                "FROM word_log_table\n" +
                "GROUP BY TUMBLE(row_time, INTERVAL '10' second ), keyword");

//        Table ss = tabEnv.sqlQuery("select * from word_log_table");
        //reportTable.execute().print();
        //System.out.println(reportTable);

        return reportTable;
    }

    private static void createInputTable(TableEnvironment tabEnv) {
        tabEnv.executeSql(
                "CREATE TABLE dwd_traffic_page_log_kafka_source\n" +
                        "(\n" +
                        "    `common` MAP<STRING, STRING> COMMENT '公共环境信息',\n" +
                        "    `page` MAP<STRING, STRING> COMMENT '页面信息',\n" +
                        "    `ts` BIGINT,\n" +
                        "    row_time AS TO_TIMESTAMP(FROM_UNIXTIME(ts / 1000, 'yyyy-MM-dd HH:mm:ss.SSS')),\n" +
                        "    WATERMARK FOR row_time AS row_time - INTERVAL '0' MINUTE\n" +
                        ") WITH (\n" +
                        "    'connector' = 'kafka',\n" +
                        "    'topic' = 'dwd-traffic-page-log',\n" +
                        "    'properties.bootstrap.servers' = 'node101:9092,node102:9092,node103:9092',\n" +
                        "    'properties.group.id' = 'gid_dws_log_search_keyword',\n" +
                        "    'scan.startup.mode' = 'earliest-offset',\n" +
                        "    'format' = 'json',\n" +
                        "    'json.fail-on-missing-field' = 'false',\n" +
                        "    'json.ignore-parse-errors' = 'true'\n" +
                        ")"
        );
    }

    private static TableEnvironment getTableEnv() {
        //环境设置
        EnvironmentSettings settings = EnvironmentSettings.newInstance()
                .inStreamingMode()
                .useBlinkPlanner()
                .build();
        TableEnvironment tabEnv = TableEnvironment.create(settings);
        //配置属性设置
        Configuration configuration = tabEnv.getConfig().getConfiguration();
        configuration.setString("table.local-time-zone","Asia/Shanghai");
        configuration.setString("table.exec.resource.default-parallelism","1");
        configuration.setString("table.exec.state.ttl","5 s");
        //返回结果
        return tabEnv;
    }

    @FunctionHint(output = @DataTypeHint("ROW<keyword STRING>"))
    public static class IkAnalyzerFunction extends TableFunction<Row> {
        public void eval(String fullWord) throws Exception{
            //中文分词
            List<String> list = AnalyzerUtil.ikAnalyzer(fullWord);
            //循环遍历输出
            for (String keyword : list) {
                collect(Row.of(keyword));
            }
        }
    }

}
